Abstract:
Optimal-control problems can give rise to boundary value problems (BVPs) whose solution contains the required control term. ParaDiag [1,2,3] and ParaOpt [4] are two algorithms to solve these optimality BVPs in a time-parallel way. The former is limited to linear problems with a symmetric system matrix, but generally scales well; the latter applies to non-linear problems, but includes a linear-system solving step that does not scale well when increasing time-parallelism.The presentation consists of two main parts. In the first, we propose algorithmic improvements and extensions to these methods that make them more generally applicable and that improve their scaling. More specifically, we extend ParaDiag\'s applicability to non-symmetric linear problems and more general control objectives [5]. We then apply these new ParaDiag preconditioners to the linear system in ParaOpt, which improves its scaling [6].The second part of the presentation discusses theoretical results about ParaDiag and ParaOpt applied to linear diffusive problems. We show how convergence for both algorithms can be studied by finding eigenvalues of related matrices and present convergence bounds that are parameterised by the time discretisation scheme(s) used. This generic approach allows us to improve the state-of-the-art coarse propagator for ParaOpt and to directly apply ParaDiag\'s analysis to the ParaOpt preconditioners we developed.[1]: S.-L. Wu and T. Zhou. Diagonalization-based parallel-in-time algorithms for parabolic PDE-constrained optimization problems. ESAIM: Control, Optimisa- tion and Calculus of Variations, 26, 2020.[2]: S.-L. Wu and J. Liu. A parallel-in-time block-circulant preconditioner for optimal control of wave equations. SIAM Journal on Scientific Computing, 42(3):A1510–A1540, 2020.[3]: M. J. Gander, J. Liu, S.-L. Wu, X. Yue, and T. Zhou. ParaDiag: parallel-in-time algorithms based on the diagonalization technique. arXiv:2005.09158 [cs, math], Apr 2021.[4]: M. J. Gander, F. Kwok, and J. Salomon. PARAOPT: A Parareal algorithm for optimality systems. SIAM Journal on Scientific Computing, 42(5):A2773–A2802, Jan 2020.[5]: A. Bouillon, G. Samaey, and K. Meerbergen. On generalized preconditioners for time-parallel parabolic optimal control. arxiv:2302.06406 [cs, math], Feb 2023.[6]: A. Bouillon, G. Samaey, and K. Meerbergen. Diagonalization-based preconditioners and generalized convergence bounds for ParaOpt. arxiv:2304.09235 [cs, math], Apr 2023.

14:00 • Université de Genève, Conseil Général 7-9, Room 1-05

Universität Zürich

Zurich Graduate Colloquium

Laura Marino (IMJ Paris)

What is... a rational tangle? abstract

15:30 • UZH Zentrum, Building KO2, Room F 150

ETH Zürich

Alice Roth Lectures

Alison Etheridge (FRS (Oxford))

Some mathematical models of evolution abstract

17:00 • ETH Zentrum, Rämistrasse 101, Zürich, Building HG, Room F 30

Wednesday, March 6

Université de Fribourg

Oberseminar Geometrie

Masoumeh Zarei (Münster)

Susceptibility of positive curvature conditions under the Ricci flow abstract

10:20 • Université de Fribourg, room Phys 2.52

ETH Zürich

Ergodic theory and dynamical systems seminar

Dr. Hao Wu (Universität Zürich)

A central limit theorem for irrational rotations of bounded type abstract

13:30 • ETH Zentrum, Rämistrasse 101, Zürich, Building HG, Room G 19.1

ETH Zürich

Algebraic Geometry and Moduli Seminar

Aitor Iribar Lopez (ETH Zürich)

Twisted products in the moduli space of abelian varieties abstract

13:30 • ETH Zentrum, Rämistrasse 101, Zürich, Building HG, Room G 43

Universität Basel

Analysis Seminar

Klaus Widmayer (Universität Zürich)

Landau damping near the Poisson equilibrium in R^3 abstract

14:15 • Universität Basel, Spiegelgasse 5, Seminarraum 05.002

Universität Zürich

Neuchatel - St.Gallen - Zurich Seminar in Coding Theory and Cryptography

Dr. Khu Vu Van (National University of Singapore)

Coding for Data Storage Systems abstract

15:15 • UZH Irchel, Winterthurerstrasse 190, Zürich, Building Y27, Room H 25

ETH Zürich

Zurich Colloquium in Applied and Computational Mathematics

Prof. Dr. Enrique Zuazua (Friedrich-Alexander-Universität Erlangen-Nürnberg)

Dynamics, Control and Numerics abstract

Abstract:
Norbert Wiener defined “Cybernetics” as “the science of control and communication in the animal and the machine”, anticipating some of the goals and the future development of Artificial Intelligence. The traditional Applied Mathematics program, combining modelling, analysis, numerical approximation, and scientific computing, when facing practical applications, must often be complemented by additional efforts to address control issues, to better understand how dynamics changes when varying free parameters. This frequently leads to new complex and fascinating analytical and computational challenges that require significant unexpected further developments. We will lecture on some recent success stories that arise when facing, for instance, source identification problems, and the regulation of collective dynamics. We shall also discuss the issue of the optimal placement of sensors and actuators, which plays a key role when designing efficient control mechanisms. Control techniques also play an unexpected relevant role in other contexts such as the large time asymptotics for partially dissipative systems in fluid mechanics. We will describe the links between these problems and their analytical and numerical treatment, as one further manifestation of the unity and interconnections of all mathematical disciplines.We shall conclude pointing towards some perspective for future research in connection with Machine Learning.We will begin by briefly discussing the origins of mathematical control theory and machine learning, emphasizing their intimate analogies and links. We will then recall some basic results on the control of linear finite-dimensional systems and the Universal Approximation Theorem. Later we will address the problem of supervised learning, formulated as a simultaneous or ensemble control problem for the so-called neural differential equations, driven by Lipschitz nonlinearities, the activation functions in the neural network ansatz for learning. We will present an iterative and constructive method, allowing to show that such an ambitious goal can be achieved, estimating the complexity of the control strategies. The very role that the nonlinear nature of the activation functions plays will be emphasized.Unnecessary technical difficulties will be avoided. Several open problems and perspectives for future research will be formulated.

16:30 • ETH Zentrum, Rämistrasse 101, Zürich, Building HG, Room E 1.2

ETH Zürich

Seminar on Stochastic Processes

Prof. Dr. Vincent Vargas (Universität Genf)

CANCELLED: Harmonic analysis of Gaussian multiplicative chaos on the circle abstract

17:15 • ETH Zentrum, Rämistrasse 101, Zürich, Building HG, Room G 43

Thursday, March 7

ETH Zürich

Nachdiplomvorlesung

Umut Çetin (London School of Economics)

Mathematics of Market Microstructure

10:15 • ETH Zentrum, Rämistrasse 101, Zürich, Building HG, Room G 43

Université de Genève

Séminaire de Topologie et Géométrie

Jean-Claude Hausmann (UNIGE)

Rigidité différentiable pour les plongements : les exemples d\'Haefliger abstract

14:15 • Université de Genève, Conseil Général 7-9, Room 1-15

ETH Zürich

Research Seminar in Statistics

Elliot Young (The University of Cambridge)

Sandwich Boosting for accurate estimation in partially linear models for grouped data abstract

16:15 • ETH Zentrum, Rämistrasse 101, Zürich, Building HG, Room G 19.1

Universität Zürich

PDE and Mathematical Physics

Dr. Luca Fresta (Universität Zürich)

Fermionic stochastic analysis abstract

16:15 • UZH Irchel, Winterthurerstrasse 190, Zürich, Building Y27, Room H 46

ETH Zürich

Talks in Financial and Insurance Mathematics

Prof. Dr. Gregoire Loeper (BNP Paribas Global Markets)

Black and Scholes, Legendre and Sinkhorn abstract

17:15 • ETH Zentrum, Rämistrasse 101, Zürich, Building HG, Room G 43

Friday, March 8

ETH Zürich

DACO Seminar

Aram-Alexandre Pooladian (NYU, US)

Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space abstract

11:15 • ETH Zentrum, Rämistrasse 101, Zürich, Building HG, Room G 43

EPF Lausanne. MA B1 11

Seminar of Analysis

Enrique Zuazua (FAU - Erlangen - Nuremberg)

CONTROL AND MACHINE LEARNING abstract

14:15 • EPF Lausanne. MA B1 11

ETH Zürich

Number Theory Seminar

Dr. Efthymios Sofos (University of Glasgow)

Multiplicative functions and applications abstract

14:15 • ETH Zentrum, Rämistrasse 101, Zürich, Building HG, Room G 43

EPF Lausanne

Statistics Seminar

Richard Gill (Leiden University)

A tale of two Lucys abstract

Abstract:
*Lucia de Berk*, a Dutch nurse, was arrested in 2001, and tried and convicted of serial murder of patients in her care. At a lower court the only hard evidence against her was the result of a probability calculation: the chance that she was present at so many suspicious deaths and collapses in the hospitals where she had worked was 1 in 342 million. During appeal proceedings at a higher court, the prosecution shifted gears and gave the impression that there was now hard evidence that she had killed one baby. Having established that she was a killer and a liar (she claimed innocence) it was not difficult to pin another 9 deaths and collapses on her. No statistics were needed any more. In 2005 the conviction was confirmed by the supreme court. But at the same time, some whistleblowers started getting attention from the media. A long fight for the hearts and minds of the public, and a long fight to have the case reopened (without any new evidence - only new scientific interpretation of existing evidence) began and ended in 2010 with Lucia’s complete exoneration. A number of statisticians played a big role in that fight. The idea that the conviction was purely based on objective scientific evidence was actually an illusion. This needed to be explained to journalists and to the public. And the judiciary needed to be convinced that something had to be done about it. *Lucy Letby*, an English nurse, was arrested in 2020 for murder of a large number of babies at a hospital in Chester, UK, in Jan 2015-June 2016. Her trial started in 2022 and took 10 months. She was convicted and given a whole life sentence in 2023. In my opinion, the similarities between the two cases are horrific. Again there is statistical evidence: a cluster of unexplained bad events, and Lucy was there every time; there is apparently irrefutable scientific evidence for two babies; and just like with Lucia de Berk, there are some weird personal and private writings which can be construed as a confession. For many reasons, the chances of a fair retrial for Lucy Letby are very thin indeed, but I am convinced she is innocent and that her trial was grossly unfair. I will try to convince you, too. I predict that it will take between 6 and 12 years before she is exonerated. Reference:https://rss.org.uk/news-publication/news-publications/2022/section-group-reports/rss-publishes-report-on-dealing-with-uncertainty-i/

15:15 • EPF Lausanne, MA A1 12

address: Alessandra Naldi Windler, Departement Mathematik, HG G 51.4, ETH Zurich, Raemistrasse 101, CH-8092 Zurich
email: bulletin@math.ch | phone: +41 44 632 3684 | url: https://math.ch

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